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Recently, integrated models of facility location and network design (FLND) problems have attracted many research attentions. This class of NP-hard problems, as the name suggests, simultaneously optimizes facility locations and the design of the underlying network. They have been a central and useful planning tool in many contexts, e.g., regional planning, distribution, energy management, etc. However, FLND problems are extremely hard to solve and computational difficulties has limited their way into the practice. In this paper, we propose three variants of a simple and efficient meta-heuristic based on variable neighborhood search method to solve the capacitated FLND problem effectively. We particularly improve the neighborhood exploration mechanism by taking advantage of exact methods within the solution framework. Computational experiments on a wide-range of test instances with up to 100 nodes and 600 links show that our approaches consistently return high quality solutions in short CPU times in comparison with the state-of-the-art of commercial solvers. [ABSTRACT FROM AUTHOR]

Proposing a robust designed facility location is one of the most effective ways to hedge against unexpected disruptions and failures in a transportation network system. This paper considers the combined facility location/network design problem with regard to transportation link disruptions and develops a mixed integer linear programming formulation to model it. With respect to the probability of link disruptions, the objective function of the model minimizes the total costs, including location costs, link construction costs and also the expected transportation costs. An efficient hybrid algorithm based on LP relaxation and variable neighborhood search metaheuristic is developed in order to solve the mathematical model. Numerical results demonstrate that the proposed hybrid algorithm has suitable efficiency in terms of duration of solution time and determining excellent solution quality. [ABSTRACT FROM AUTHOR]

Abstract: This article presents a mixed-integer model to optimize the location of facilities and the underlying transportation network at the same time to minimize the total transportation and operating costs. In this problem, it is assumed that for connecting two nodes, there are several types of links in which their capacity, transportation and construction costs are different. The developed model has various applications in telecommunication, emergency, regional planning, pipeline network, energy management, distribution, to just name a few. To solve the model effectively, this paper also proposes a fix-and-optimize heuristic based on the evolutionary fire-fly algorithm. Finally, to validate the model and evaluate the algorithm’s performance, a series of test instances with up to 100 nodes and 600 candidate links with three different levels of quality are reported. [Copyright &y& Elsevier]

Abstract: This paper presents a model for the budget-constrained dynamic (multi-period) uncapacitated facility location–network design problem (DUFLNDP). This problem is concerned with the determination of the optimal locations of facilities and the design of the underlying network simultaneously in which there is a budget constraint on investment for opening the facilities and constructing (activating) links for each time period during the planning horizon. The objective is to minimize the total travel costs for customers and operating costs for facilities and network links. Furthermore, a greedy heuristic and a fix-and-optimize heuristic based on simulated annealing and exact methods (Branch & Bound and cutting methods) are proposed to solve the model. The performance of the proposed algorithms were tested on extensive randomly generated instances and compared with the CPLEX solver. The budget-constrained DU FLNDP has a lot of important applications which as one of them, the accessibility of health care facilities in Illam Province of Iran is investigated. [Copyright &y& Elsevier]